iraq and afghanistan war veterans with reintegration problems: differences by veterans affairs...
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ORIGINAL ARTICLE
Iraq and Afghanistan War Veterans with Reintegration Problems:Differences by Veterans Affairs Healthcare User Status
Nina A. Sayer • Robert J. Orazem • Siamak Noorbaloochi • Amy Gravely •
Patricia Frazier • Kathleen F. Carlson • Paula P. Schnurr • Heather Oleson
� The Author(s) 2014. This article is published with open access at Springerlink.com
Abstract We studied 1,292 Iraq and Afghanistan War
veterans who participated in a clinical trial of expressive
writing to estimate the prevalence of perceived reintegra-
tion difficulty and compare Veterans Affairs (VA) health-
care users to nonusers in terms of demographic and clinical
characteristics. About half of participants perceived rein-
tegration difficulty. VA users and nonusers differed in age
and military background. Levels of mental and physical
problems were higher in VA users. In multivariate analysis,
military service variables and probable traumatic brain
injury independently predicted VA use. Findings demon-
strate the importance of research comparing VA users to
nonusers to understand veteran healthcare needs.
Keywords Veterans � Healthcare service needs � Mental
health � Posttraumatic stress disorder � Traumatic brain
injury � Department of Veterans Affairs Healthcare
Introduction
United States (US) combat operations in Afghanistan, Iraq
and neighboring countries, referred to as Operation
Enduring Freedom (OEF), Operation Iraqi Freedom (OIF),
and Operation New Dawn (OND), taken together comprise
the longest war the US has fought since the Vietnam War
and the first extended war to depend on an all-volunteer
military. Identifying and treating the needs of service
members and veterans who served in these operations is a
high priority for both the Department of Defense (DoD)
and the Department of Veterans Affairs (VA). It is also a
priority for clinicians outside of these two FederalPortions of these data were presented at the 2013 American
Psychological Association Annual Convention.
N. A. Sayer (&) � R. J. Orazem � S. Noorbaloochi �A. Gravely � H. Oleson
Center for Chronic Disease Outcomes Research, Minneapolis
VA Healthcare System, One Veterans Drive, Minneapolis,
MN 55417, USA
e-mail: [email protected]
N. A. Sayer � S. Noorbaloochi
Department of Medicine, University of Minnesota, Minneapolis,
MN, USA
N. A. Sayer
Departments of Psychiatry, University of Minnesota,
Minneapolis, MN, USA
P. Frazier
Department of Psychology, University of Minnesota,
Minneapolis, MN, USA
K. F. Carlson
Center to Improve Veteran Involvement in Care, Portland VA
Medical Center, Portland, OR, USA
K. F. Carlson
Department of Public Health and Preventive Medicine, Oregon
Health and Science University, Portland, OR, USA
P. P. Schnurr
National Center for PTSD, White River Junction, VT, USA
P. P. Schnurr
Geisel School of Medicine at Dartmouth, Hanover, NH, USA
123
Adm Policy Ment Health
DOI 10.1007/s10488-014-0564-2
healthcare systems who provide services to veterans, but
may not have expertise on deployment-related health
concerns or easy access to resources for combat veterans.
Research indicates that US service members returning
from the wars in Iraq and Afghanistan carry a high burden
of mental health disorders, with posttraumatic stress dis-
order (PTSD) being particularly common (Hoge et al.
2004; Hoge et al. 2006; Milliken et al. 2007; Smith et al.
2008). A 2010 systematic review reported that PTSD
prevalence estimates ranged between 10.3 and 17 % in
studies based on surveys of combat troops formerly
deployed to Iraq (Sundin et al. 2010). The wars in Iraq and
Afghanistan have also heightened concern about the
sequelae of traumatic brain injury (TBI), which some have
designated the ‘‘signature injury’’ of these wars because of
its prevalence relative to prior wars (DePalma et al. 2005;
Okie 2006). Findings based on surveys of individuals for-
merly deployed to Afghanistan and Iraq suggest that
10–23 % may have had a deployment-related TBI (Sayer
et al. 2014). Furthermore, with one notable exception
(Schell and Marshall 2008), research indicates that the
prevalence of reported mental health concerns and TBI
increases as time since deployment increases (Milliken
et al. 2007; Polusny et al. 2011; Sundin et al. 2010).
Indeed, it is likely that Iraq and Afghanistan war veterans
will have elevated healthcare needs long after US military
operations in these countries cease.
Importantly, even in the absence of a diagnosed
deployment-related health condition, individuals formerly
deployed to combat zones may have difficulty transitioning
from military to civilian roles. In a national survey of OEF/
OIF veterans who use VA healthcare, Sayer et al. (2010)
found that at least 25 % were having some to extreme
difficulty in major life domains after their deployments
including social functioning, productivity, community
involvement and self-care. Although these problems were
more common in those with probable PTSD, high pro-
portions of the OEF/OIF veterans faced challenges in
multiple domains of functioning and community involve-
ment regardless of their mental health status (Sayer et al.
2010). Policy makers and providers need a better under-
standing of not only the mental and physical health burdens
but also the functional problems in veterans returning from
war to design strategies to promote their full and produc-
tive participation in civilian life.
Studies describing postdeployment healthcare needs of
those formerly deployed to Iraq and Afghanistan have been
based primarily on active duty service members who
access the military health system (Hoge et al. 2004, 2006;
Milliken et al. 2007; Smith et al. 2008) or veterans seeking
VA healthcare (Sayer et al. 2010; Scholten et al.2012; Seal
et al. 2009, 2010; Taylor et al. 2012). Although this
research is informative, it leaves unanswered questions
concerning the health and postdeployment reintegration of
OEF/OIF/OND veterans who do not make use of VA
healthcare after their military discharge. Under the
National Defense Authorization Act of 2008, all OEF/OIF/
OND veterans are eligible for five years of free VA
healthcare for any condition possibly related to combat
service (U.S. Department of Veterans Affairs 2011).
However, not all OEF/OIF/OND veterans have enrolled in
and used the VA. At the time of this writing, 58 % of
eligible Iraq and Afghanistan veterans had used VA
healthcare since their military discharge (U.S. Department
of Veterans Affairs, Epidemiology Program 2014), com-
pared with roughly 30 % of Vietnam and 25 % of Korean
and WWII veterans (U.S. Department of Veterans Affairs
2010a).
Research based on veterans of prior wars has identified
meaningful differences between veterans who used VA
healthcare and those who did not. For example, it has been
reported that veterans who used VA were more likely to be
nonwhite, of lower socioeconomic status, and to have a
higher prevalence of disability, major chronic conditions,
and obesity than veterans who did not use VA (Agha et al.
2000; Hynes et al. 2007; Koepsell et al. 2009; Littman et al.
2012; Nelson et al. 2007). It is unknown whether these
patterns of differences in sociodemographics and disease
burden extend to OEF/OIF/OND veterans. OEF/OIF/OND
veterans have enrolled in VA for healthcare at a much
higher rate than veterans from prior service eras, probably
because of large-scale outreach efforts accompanying the
National Defense Authorization Act of 2008. Because of
this, there may be fewer differences between OEF/OIF/
OND veterans who enroll in VA and those who do not. If
there are fewer differences, then research based on VA
samples of OEF/OIF/OND veterans may generalize to
those who do not use VA healthcare. Regardless, an
understanding of the postdeployment healthcare needs of
VA users and nonusers is necessary to inform service
delivery for those who receive healthcare within and out-
side of the VA healthcare system.
This study makes use of data collected as part of a large,
national randomized clinical trial (RCT) of expressive
writing in OEF/OIF/OND veterans with self-reported
reintegration difficulty. We focused on veterans who
believed that they had reintegration difficulty because they
would be more likely to also be interested in receiving help
to adjust to civilian life. Our first objective was to estimate
the prevalence of perceived overall reintegration difficulty
in the entire population of OEF/OIF/OND veterans. The
remaining two objectives focused only on veterans who
believed they were having reintegration difficulty. Specif-
ically, our second objective was to compare sociodemo-
graphic characteristics and the mental and physical health
of OEF/OIF/OND veterans with perceived reintegration
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123
difficulty who used to those who do not use VA healthcare.
Our third objective was to identify predictors of VA
healthcare user status among veterans with perceived
reintegration difficulty.
Methods
Data Source
This study used variables from the DoD Defense Man-
power Data Center (DMDC) roster of all OEF/OIF/OND
veterans who had left active duty military service, and
assessment data from a RCT of expressive writing in OEF/
OIF/OND veterans with perceived reintegration difficulty.
This study was approved by the Minneapolis VA Health-
care System and University of Minnesota institutional
review boards and U.S. Army Medical Research and
Materiel Command Human Research Protection Office.
Participants
Figure 1 displays the pathway from our recruitment pool to
inclusion in our study. We recruited the sample of veterans
from the DMDC roster, which included 1,396,477 veterans
at the time of this study. We randomly selected a gender-
stratified sample of 20,000 veterans. We oversampled
women, who comprised 12 % of the population, such that
they comprised 30 % of our potential recruitment pool.
We used mail survey methods that involved repeat mail-
ing to nonresponders and a $5 monetary incentive (Dillman
2000) to assess inclusion and exclusion criteria in our
recruitment pool. We stopped recruitment after contacting
15,686 veterans because we had reached our target sample
size. Inclusion criteria were: self-report of ‘‘at least a little
difficulty readjusting back into civilian life’’ assessed with a
general single item used in prior research (Sayer et al. 2010);
internet access; and providing an email address and tele-
phone number. We used subjective report of overall reinte-
gration difficulty because we were interested in identifying a
sample who perceived a need for help with reintegration
problems regardless of whether these problems were objec-
tively clinically significant. In preliminary research, we
found that veterans who reported at least ‘‘a little difficulty’’
reintegrating on this single item had poorer mental health and
more functional difficulties than those who reported ‘‘no
difficulty’’ reintegrating into community life. Exclusion
criteria included severe depression as identified by the
patient health questionnaire-eight-item depression scale
(PHQ-8; Kroenke et al. 2009). We excluded individuals with
severe depression because prior studies found that those with
severe depression did not benefit from the intervention tested
in our RCT (Baikie et al. 2012; Kovac and Range 2002).We
also asked veterans if they would be interested in partici-
pating in our online expressive writing intervention and
invited those who were eligible and interested to participate.
Of the 15,686 veterans contacted (our effective recruit-
ment pool), 8,207 (52 %) returned our eligibility survey
within the study timeframe, 4,317 (53 %) of whom
reported ‘‘at least a little difficulty readjusting back into
civilian life’’ on the general single item used to assess study
eligibility that was described above. Among those with any
self-reported reintegration difficulty, 618 (14 %), including
371 (9 %) who screened positive for severe depression, did
not meet our other inclusion/exclusion criteria and 2,407
(56 %) were not interested in participating in our online
RCT as indicated by either their response to our survey
question assessing interest or nonresponse to our invitation
to participate. Almost two-thirds (n = 829; 64 %) of the
1,292 veterans included in our sample had sought VA
healthcare according to the DMDC roster.
Measures
DMDC roster variables were available for veterans in our
recruitment pool. All the other measures listed below were
available for the 1,292 veterans included in our RCT.
3,025 eliminated because:
N= 371 severe depression N = 63 no internet N = 184 no phone
N = 2,407 not interested in participation
Iraq and Afghanistan War Veterans surveyed to determine
eligibility N=15,686
Eligibility assessed N=8,207
Reported “at least a little reintegration difficulty”
N=4,317
Study SampleN = 1,292
VA userN = 834
VA nonuserN = 458
Fig. 1 Pathway from recruitment to study sample
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123
DMDC Roster Variables
We used the following DMDC roster variables: gender,
race, military branch, military component, time since dis-
charge, and VA user status.
Other Sociodemographic Characteristics
We assessed age, education, employment and student sta-
tus, income, marital and parental status, service connection,
and military rank. We also obtained more detailed infor-
mation regarding race and ethnicity than was available in
the DMDC roster.
Trauma History
We assessed lifetime trauma history using the posttrau-
matic stress diagnostic scale (PDS; Foa 1995) and combat
exposure using the combat experiences scale from the
Deployment Risk and Resilience Inventory (DRRI; King
et al. 2003; Vogt et al. 2008).
Psychological Distress
We measured psychological distress with the Brief
Symptom Inventory (BSI-18; Derogatis 2000) which con-
tains 18 items that assess depression, anxiety, and soma-
tization and together yield a global severity index.
Participants indicated the degree to which each symptom
caused them distress in the past 2 weeks on a 5-point scale
ranging from 0 (not at all) to 4 (extremely). Total scores,
which are formed by averaging the scores across the items,
range from 0 to 4, with higher scores indicating greater
distress. Internal consistency (Cronbach’s alpha) in the
study sample was 0.93.
Anger
The BSI Hostility subscale, a separate 5-item subscale from
the BSI, is a measure of anger and anger expression.
Response format and scoring rules were the same as those
employed for the BSI-18. The hostility subscale, like the
other BSI scales, has strong psychometric properties
(Derogatis 1993). Cronbach’s alpha in the study sample
was 0.77.
Physical Symptoms
The Pennebaker Inventory of Limbic Languidness (PILL;
Pennebaker, 1982) is a 54-item scale that assesses the
frequency of occurrence of common physical symptoms
and sensations. In this study we removed two PILL items
that overlapped with BSI somatization items and one that
was highly redundant with another PILL item so that our
measure consisted of 51 items. In addition, for ease of
administration as part of this assessment battery, we used
the same time frame and response format for the PILL that
we used for the BSI. Total scores were determined by
counting the number of symptoms that were rated ‘‘2’’
(‘‘moderately’’ distressing or bothersome) or higher. Thus,
total scores ranged from 0 to 51, with higher scores indi-
cating endorsement of a greater number of physical
symptoms at moderate to extreme levels. Cronbach’s alpha
in our sample was 0.95.
Probable PTSD
We assessed probable PTSD using the PTSD checklist-
military version (PCL-M; Weathers et al. 1995). The PCL-
M consists of the 17 DSM-IV PTSD symptoms that are
rated on a 5-point Likert scale ranging from 1 (not at all) to
5 (extremely). Consistent with DSM-IV criteria for PTSD,
we defined probable PTSD cases as those who reported
over the past month at least one symptom of moderate or
greater severity from cluster B (reexperiencing symptoms),
three symptoms of moderate or greater severity from
cluster C (avoidance symptoms), and two symptoms of
moderate or greater severity from cluster D (hyperarousal
symptoms).
Probable Traumatic Brain Injury (TBI)
Those who indicated on the Combat Experiences Scale
that they were injured or wounded in combat were
administered the first two questions from the Brief TBI
Screen (Schwab et al. 2007). Probable TBI was defined as
endorsement of both: (1) ‘‘During any of your deploy-
ments, were you injured from any of the following:
fragment/shrapnel wound above the shoulder, bullet
wound above the shoulder, vehicular accident or crash
(any type of vehicle, including airplane), fall, blast/
explosion (improvised explosive device, RPG, land mine,
grenade, mortar, artillery, etc.), other type of blow to the
head’’, and (2) ‘‘Did any injury you received while
deployed result in any of the following immediately
afterwards: Being dazed, confused, or ‘‘seeing stars’’; not
remembering the event; losing consciousness; head injury
or concussion.’’
Reintegration Difficulty
We used the Military to Civilian Questionnaire (M2C-Q) to
assess past month reintegration difficulty (Sayer et al.
2011). The M2C-Q has 16-items that assess difficulty in the
following reintegration domains: social relations (8 items),
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productivity (e.g., schooling, employment; domestic life; 3
items), community or civic engagement (2 items), per-
ceived meaning in life (1 item), and self-care and leisure (2
items). Responses range from 0 (no difficulty) to 4 (extreme
difficulty); four items (e.g., parenting problems) also offer a
‘‘not applicable’’ response option. Total scores were
formed by summing across items and dividing by the
number of completed items, with higher scores indicating
greater reintegration difficulty. Initial research supports the
construct and factor validity of scale scores (Sayer et al.
2011). Cronbach’s alpha in this sample was 0.92.
Social Support
Perceived social support over the past month was assessed
with the Post-Deployment Social Support Scale from the
DRRI (King et al. 2003). This scale measures the extent to
which family, friends, coworkers, employers, and the
community provide emotional and instrumental support.
Each of the 15 items is scored on a 5-point scale with
responses ranging from 1 = ‘‘strongly agree’’ to
5 = ‘‘strongly disagree.’’ Total scores were formed by
adding across items. The scale scores have high internal
consistency and associations with mental health outcomes
support construct validity (Vogt et al. 2008). Cronbach’s
alpha in the study sample was 0.85.
Life Satisfaction
Global life satisfaction over the past month was measured
with the satisfaction with life scale (SWLS; Diener et al.
1985). The five items were rated on a 7-point scale ranging
from 1 = ‘‘strongly disagree’’ to 7 = ‘‘strongly agree’’.
Two-month test–retest reliability has been found to be
0.82. The one factor structure of the SWLS has been
established via exploratory factor analysis and the validity
of the SWLS scores have been found to exceed other
comparable measures of well-being (Frazier et al. 2003).
Cronbach’s alpha in the study sample was 0.92.
Binge Drinking and Tobacco Use
The following questions were used to assess binge drink-
ing: (1) ‘‘Have you had any alcohol in the past month?’’;
(2) ‘‘Over the past month, how many days per week did
you have a drink containing alcohol on average?’’; and (3)
‘‘Over the past month, how many times did you have 5 (for
men)/4 (for women) or more drinks on one occasion?’’
These questions were taken from the Behavioral Risk
Factor Surveillance System (BRFSS) survey (Naimi et al.
2003) with the one modification being that we defined
binge drinking differently for men than for women because
of gender differences in gastric metabolism of alcohol
(Wechsler et al. 1995). Binge drinking was defined as
consumption of 4 or 5 or more drinks on at least one
occasion in the past 30 days for women and men, respec-
tively. In addition, we asked participants how many ciga-
rettes per day they smoked on average over the past month.
Health Services Use
We asked participants to indicate the number of times they
have seen a medical professional (doctor, nurse, psychol-
ogist, psychiatrist, social worker, rehabilitation specialist of
any kind, etc.) for a physical illness or injury or a medical
professional (doctor, nurse, psychologist, psychiatrist,
social worker, etc) for a mental health concern in the past
3 months. Responses were dichotomized to represent any
physical or mental healthcare use in the past 3 months.
Data Analysis
This was a stratified random sample with oversampling of
women. Therefore, we derived all estimates based on
weighted analyses. Weights were generated to reflect the
inverse probability of participants from specific subpopu-
lations being sampled.
To estimate the prevalence of perceived reintegration
difficulty in the population of Iraq and Afghanistan veter-
ans (Objective 1), we stratified the recruitment pool
(N = 15,686) into four groups based on gender (male,
female) and VA user status (yes, no). We then constructed
a stratified logistic regression model of perceived reinte-
gration difficulty (yes, no) among the 8,207 responders to
our eligibility survey based on the DMDC roster variables.
This model was used to predict perceived reintegration
difficulty (yes, no) among the 7,479 eligibility survey
nonresponders. To increase the precision of our estimate of
perceived reintegration difficulty beyond our recruitment
pool, we divided each gender by user group into 96 strata
based on the other four variables included in the DMDC
roster and projected these proportions to the population
based on the sizes of these strata in the entire population of
OEF/OIF/OND veterans.
Objectives 2 and 3 focused on the subgroup of Iraq and
Afghanistan veterans with perceived reintegration diffi-
culty. To extrapolate from study measures based on the
1,292 included in our RCT to the subpopulation of OEF/
OIF/OND veterans with perceived reintegration difficulty,
we modeled two forms of potential bias: (a) nonresponse to
our eligibility survey, and (b) among survey responders
with perceived reintegration difficulty, nonparticipation in
our RCT. We used logistic regression to estimate the
propensity of both forms of potential bias based on DMDC
roster variables available for our recruitment pool. Spe-
cifically, for nonresponse adjustment, we constructed 9
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Table 1 Sociodemographic characteristics of Iraq and Afghanistan war veterans with perceived reintegration difficulty by VA user status
Population VA nonuser VA user
Characteristic Weighted proportion
or mean
SE Weighted proportion
or mean
SE Weighted proportion
or mean
SE
Age [40 years (%)*** 28.95 0.90 23.43 1.43 31.87 1.16
Female (%) 10.78 0.003 10.92 0.003 10.68 0.003
Race (%)
White only 65.68 1.64 66.77 2.98 65.10 1.94
Black only 11.75 1.05 10.82 1.85 12.24 1.28
Asian only 3.28 0.64 2.71 1.10 3.58 0.79
Native American only 1.57 0.43 1.10 0.69 1.83 0.55
Multiracial/other 4.22 0.73 5.24 1.50 3.68 0.77
Not reported 13.51 1.23 13.37 2.29 13.58 1.44
Hispanic ethnicity (%) 15.82 1.31 15.45 2.41 16.01 1.54
Marital status (%)
Never married/single 23.93 1.51 25.05 2.81 23.34 1.77
Married/partnered 60.13 1.65 59.92 2.95 60.24 1.98
Divorced/separated 15.61 1.26 14.78 2.27 16.04 1.51
Widowed 0.33 0.18 0.25 0.21 0.37 0.25
Has one or more children (%) 62.80 1.61 59.24 2.80 64.68 1.96
Education (%)
High school diploma or GED 12.22 1.23 13.46 2.33 11.57 1.42
Some college 46.23 1.70 49.55 3.08 44.48 2.03
College diploma 30.53 1.53 27.18 2.67 32.31 1.86
Advanced degree 9.14 0.77 8.77 1.14 9.34 1.01
Other 1.87 0.41 1.04 0.44 2.31 0.58
Student past 3 months (%) 34.74 1.66 36.47 3.03 33.83 1.96
Working past 3 months (%) 76.67 1.45 79.78 2.52 75.03 1.77
Income (%)
$10,000 or less 6.29 0.91 6.09 1.66 6.40 1.07
$10,001 to $20,000 11.74 1.19 12.58 2.28 11.30 1.36
$20,001 to $40,000 23.53 1.51 21.27 2.66 24.72 1.82
$40,001 to $60,000 21.32 1.44 19.02 2.49 22.53 1.76
More than $60,000 28.45 1.31 32.12 2.35 26.52 1.58
Prefer not to answer 8.67 0.99 8.93 1.91 8.53 1.12
Service branch (%)***
Army 59.88 1.64 51.59 3.05 64.27 1.92
Marines 18.22 1.40 23.95 2.77 15.18 1.56
Navy 11.86 0.91 11.91 1.58 11.83 1.11
Air force 10.04 0.76 12.55 1.36 8.71 0.92
Military rank (%)
Enlisted 88.61 0.94 87.48 1.65 89.21 1.14
Warrant officer 1.00 0.30 0.75 0.37 1.13 0.42
Officer 10.39 0.90 11.78 1.63 9.65 1.08
Military component (%)
Active duty 58.29 1.69 56.75 3.07 59.11 2.01
Reserves/national guard 38.29 1.67 40.00 3.04 37.38 1.98
Othera 3.42 0.57 3.25 0.95 3.51 0.70
Years since deployment (M)** 5.85 0.08 5.55 0.15 6.01 0.09
Service connected for mental health
condition (%)***
19.51 1.30 6.55 1.45 26.38 1.84
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123
propensity classes per gender: 3 based on the estimated
propensity of nonresponse to the eligibility survey, and
within these 3 strata, an additional 3 based on the estimated
propensity of nonparticipation in the RCT. All subsequent
analyses adjusted for these propensity strata and then
weighted to the population of those with perceived rein-
tegration difficulty.
Objective 2 focused on sociodemographic and clinical
differences between VA users and nonusers. To address
objective 2, we tested for differences in demographic
characteristics between VA users and nonusers using
stratified Chi square tests and stratified regression. Next,
we tested for differences in clinical characteristics between
VA users and nonusers while controlling for observed
demographic differences using stratified logistic regression
with adjustment based on propensity analysis.
Objective 3 involved identifying unique predictors of
VA user status. To address this objective, we used multi-
variate stratified logistic regression. We included in these
models only those variables that were significantly asso-
ciated with VA user status in bivariate analyses at P \ 0.05
(see Tables 1 and 2).
All tables include weighted estimates. We used SAS 9.3
for all computations.
Results
Reintegration Difficulty in OEF/OIF/OND Veterans
The estimated prevalence of at least a little reintegration
difficulty in the OEF/OIF/OND population was 54 %
(95 % CI 0.53–0.55). The estimated prevalence of reinte-
gration difficulty was higher among VA users (62 %; 95 %
CI 61–63 %) than among those who did not use VA
healthcare (45 %; 95 % CI 44–47 %) (p \ 0.0001).
Sociodemographic Characteristics by VA User Status
Table 1 displays sociodemographic characteristics in the
population of OEF/OIF/OND veterans with perceived
reintegration difficulty and differences by VA user status.
A larger proportion of veterans who used VA healthcare
were 40 years or older. A larger proportion of VA users
had served in the Army, whereas a larger proportion of
nonusers had served in the Marines or Air Force. VA users
had on average been discharged from military service for
6 months longer than nonusers. Additionally, a larger
proportion of VA users reported receiving VA benefits for
military-related (referred to as ‘‘service connected’’) men-
tal and physical health conditions.
Clinical Characteristics by VA User Status
Table 2 displays clinical characteristics in the population of
OEF/OIF/OND veterans with perceived reintegration diffi-
culty and differences by VA user status. There was no dif-
ference in terms of lifetime trauma history. However, VA
users reported higher levels of combat exposure. Perhaps not
surprisingly based on this fact, VA users were also more
likely to meet study criteria for probable TBI and PTSD.
They also reported higher levels of psychological distress,
physical symptoms, and reintegration difficulty. There were
no differences in anger, perceived social support, or life
satisfaction. Proportions of alcohol use, binge drinking and
smoking were similarly high across groups. The differences
in combat exposure, prevalence of probable PTSD, preva-
lence of probable TBI, distress, physical symptoms, and
reintegration difficulty between VA users and VA nonusers
remained significant when we adjusted for differences in
age, military branch, and time since deployment (data not
shown). Perhaps reflecting these clinical differences between
VA users and nonusers, VA users were much more likely to
report having sought medical care for physical or mental
health problems over the past three months.
Predictors of VA User Status
Table 3 presents results from multivariate analysis evalu-
ating the unique predictors of VA user status among vet-
erans with perceived reintegration difficulty. As can be
seen, service branch, service-connected mental and physi-
cal health conditions, time since deployment, and probable
TBI were independent predictors of VA user status. Those
Table 1 continued
Population VA nonuser VA user
Characteristic Weighted proportion
or mean
SE Weighted proportion
or mean
SE Weighted proportion
or mean
SE
Service connected for physical health
condition (%)***
46.54 1.56 22.34 2.40 59.38 2.02
VA Department of Veterans Affairs, GED general equivalency diploma
* p \ 0.05; ** p \ 0.01; *** p \ 0.001a Other included inactive ready reserve, civilian or government employee, and other
Adm Policy Ment Health
123
who served in the Army were more than twice as likely to be
VA users than those who served in the Air Force or Marines.
As time since deployment increased, the likelihood of being
a VA user increased. Those with service- connected mental
and physical health conditions were also two to four times
more likely to be VA users. Last, veterans with probable
TBI were more than twice as likely to be VA users.
Discussion
We estimate that about half of Iraq and Afghanistan vet-
erans perceived at least a little reintegration difficulty and
therefore might have felt the need for help readjusting to
civilian life. Interestingly, on average almost 6 years had
passed since military discharge among veterans with per-
ceived reintegration difficulty. This indicates that reinte-
gration problems are not transient in some veterans and,
therefore, may not resolve without intervention.
Unlike studies based on samples from prior war eras
(Agha et al. 2000; Hynes et al. 2007; Koepsell et al. 2009;
Littman et al. 2012; Nelson et al. 2007), we did not find
that VA users differed from nonusers in terms of minority
or indicators of socioeconomic status. The fact that
employment levels were similar across groups suggests that
lack of employer-based health insurance may be less of a
factor in the decision to use VA healthcare among this
newest generation of veterans than among veterans of prior
military service eras. Instead, we found that factors related
to military service, including military service branch, time
since discharge, and combat exposure were associated with
VA user status. We find it interesting that military branch
was associated with VA user status. It may be that VA’s
outreach efforts are stronger in the Army than in other
branches of the military or that military culture differs by
branch and therefore that outreach messages need to be
tailored specifically for Marines and Air Force troops. The
finding that service-connected disability predicted VA user
status was consistent with prior research (Hynes et al.
2007). This is not surprising given that veterans with ser-
vice-related disabilities have the highest priority for VA
healthcare and may also quality for reduced or no copays.
Also consistent with prior studies that had identified poorer
health status in VA users (Agha et al. 2000; Koepsell et al.
2009; Littman et al. 2012), we found that VA users had
greater mental and physical health burden than VA non-
users. In particular, OEF/OIF/OND veterans with per-
ceived reintegration difficulty who had used VA healthcare
Table 2 Clinical characteristics of Iraq and Afghanistan war veterans with perceived reintegration difficulty by VA user status
Population VA nonuser VA user
Characteristic Weighted
proportion or mean
SE Weighted
proportion or mean
SE Weighted
proportion or mean
SE
Trauma exposure (M) 3.68 0.07 3.56 0.12 3.74 0.09
Combat exposure (M)*** 5.89 0.14 5.16 0.25 6.28 0.18
Probable TBI (%)*** 10.07 1.05 3.19 1.13 13.71 1.49
Probable PTSD (%)** 34.95 1.66 27.88 2.88 38.69 2.03
Distress (M)** 1.04 0.03 0.94 0.05 1.09 0.03
Anger (M) 1.16 0.03 1.11 0.05 1.20 0.03
Physical symptoms (M)** 10.55 0.32 9.19 0.55 11.25 0.40
Social support (M) 53.31 0.37 54.29 0.70 52.79 0.43
Life satisfaction (M) 20.74 0.28 21.33 0.50 20.43 0.33
Reintegration difficulty (M)* 1.41 0.03 1.31 0.06 1.46 0.04
Any alcohol use past month (%) 75.07 1.48 76.29 2.64 74.43 1.78
Binge drinking past month (%) 50.41 1.73 49.87 3.16 50.70 2.05
Daily cigarette use past month (%)
None 75.72 1.55 75.65 2.83 75.75 1.83
20 or fewer 20.24 1.46 20.68 2.69 20.01 1.73
21 or more 4.04 0.72 3.67 1.26 4.24 0.89
Any mental health clinic visits in past
3 months (%)***
26.51 1.48 15.85 2.19 32.16 1.95
Any physical health clinic visits in past
3 months (%)***
47.35 1.68 38.56 2.91 52.00 2.06
VA Department of Veterans Affairs, TBI traumatic brain injury, PTSD posttraumatic stress disorder
* p \ 0.05; ** p \ 0.01; *** p \ 0.001
Adm Policy Ment Health
123
were more likely to have probable TBI and PTSD, and
reported higher levels of psychological distress, physical
symptoms, and reintegration difficulty. Military service-
related variables and probable TBI were independent pre-
dictors of VA user status in the multivariate model.
The VA has considerable expertise in and dedicated
resources for the assessment and treatment of deployment-
related problems, including TBI and PTSD. Our findings
lend further support for the importance of maintaining this
capacity. Importantly, however, although many of the
assessed clinical problems were more prevalent in VA
users, they were not absent in nonusers. The possible
unmet healthcare needs of veterans with deployment-rela-
ted difficulties who do not use VA healthcare is a signifi-
cant public health concern. In fact, the prevalence of
probable PTSD exceeded 25 % in VA nonusers with at
least a little perceived reintegration difficulty. Although not
necessarily related to deployment, the high prevalence of
binge drinking in VA users and nonusers also warrants
concern. Thus, providers in the private sector should be
aware of postdeployment and other common health prob-
lems in returning veterans and be prepared to help them
access the VA healthcare system if they do not have the
expertise to address these difficulties in their practice
setting.
Taken together, our results suggest that findings from
research based on samples of Iraq and Afghanistan veterans
who use VA may not generalize to veterans who do not use
VA services. The same was true of research based on
veterans from prior military service eras. Overall, there
remain significant gaps in our understanding of the
healthcare needs of Iraq and Afghanistan veterans who do
not seek VA healthcare because most research on veterans
is conducted by VA researchers studying VA users. Indeed,
this study underscores the importance of conducting
research on VA nonusers to obtain a more complete picture
of the healthcare needs of US veterans and to help ensure
that all veterans have access to needed services.
Limitations
We used DMDC roster variables to estimate the prevalence
of perceived reintegration difficulty in the population of
OEF/OIF/OND veterans based on responses to our eligi-
bility survey. Unfortunately, we did not have other vari-
ables for all veterans included in our recruitment pool.
Furthermore, our method for extrapolating from eligibility
survey responders to nonresponders was based on the
assumption that the relationship between perceived rein-
tegration difficulty and DMDC roster variables was the
same in both groups. Although we believe it to be rea-
sonable, this assumption could not be verified. A related
limitation is that we used DMDC roster variables to adjust
for potential bias associated with nonresponse to our survey
and nonparticipation in our RCT among those who per-
ceived reintegration difficulty. It is, however, likely that
there were other differences between eligibility survey
nonresponders and responders and between veterans who
did not participate and those who did participate in our
RCT for which we were not able to adjust. For example,
the exclusion of those with severe depression in our RCT
may have resulted in lower estimates of mental and phys-
ical health symptoms than are actually present in the
population of veterans with perceived reintegration diffi-
culty. Thus, further research is needed to confirm or
improve upon these estimates.
We used a single item to identify veterans who per-
ceived themselves as having reintegration difficulty and
thus might be interested in and benefit from help for
readjustment issues. However, postdeployment reintegra-
tion is a complex, multi-faceted construct (Resnik et al.
2012) and we did not assess the level and types of
impairments represented by those who reported ‘‘at least a
little’’ reintegration difficulty compared to those who
reported no reintegration difficulty. Another limitation was
that we examined differences by VA user status among
Table 3 Multivariate analysis of association between veteran char-
acteristics and use of department of Veterans affairs healthcare among
veterans with perceived reintegration difficulty
Variable Adjusted
odds ratio
95 % CI
Age [40 years 1.11 0.83–1.48
Service branch
Army vs. air Force*** 2.32 1.51–3.57
Air force vs. navy 0.65 0.39–1.11
Air force vs. marines 1.00 0.57–1.75
Army vs. navy 1.52 0.97–2.37
Army vs. marines*** 2.33 1.46–3.71
Navy vs. marines 1.53 0.87–2.69
Years since deployment* 1.08 1.01–1.15
Service connected for mental health
condition**
2.40 1.36–4.24
Service connected for physical health
condition****
4.10 2.85–5.91
Probable TBI* 2.66 1.16–6.11
Probable PTSD 1.43 0.85–2.38
Distress 1.13 0.74–1.72
Physical symptoms 0.98 0.96–1.01
Reintegration difficulty 0.93 0.70–1.22
CI confidence interval, TBI traumatic brain injury, PTSD posttrau-
matic stress disorder
* p \ 0.05; ** p \ 0.01; *** p \ 0.001; **** p \ 0.0001
Adm Policy Ment Health
123
veterans with perceived reintegration difficulty rather than
among the entire population of OEF/OIF/OND veterans.
Thus, findings regarding differences by VA user status
probably do not generalize to OEF/OIF/OND veterans who
do not believe they have any reintegration problems.
Another limitation is that we determined VA user status at
one point in time only. However, VA user status likely
changes over time and some of those classified as VA
nonusers may have subsequently become VA users. A final
limitation is that we did not assess some key variables
related to access, including how far veterans lived from a
VA, private insurance coverage and dual use of VA and
other health care systems. These are variables that should
be included in future studies that compare VA users and
nonusers as they have implications for the planning and
coordination of healthcare delivery.
Conclusions
This study focused on veterans with perceived reintegration
difficulty, which we estimate to be about half of the OEF/
OIF/OND veteran population. It is the first study of which we
are aware that compared OEF/OIF/OND VA users to non-
users. Most demographic differences between groups were
related to veterans’ military service. There were meaningful
clinical differences between groups, with greater proportions
of VA users reporting military-related problems including
probable PTSD and TBI and higher symptom levels than VA
nonusers. However, clinical problems were not absent in VA
nonusers who reported reintegration difficulty; binge
drinking and probable PTSD were particularly prevalent in
this group. This research confirms that findings describing
health and adjustment problems in VA healthcare users
cannot be generalized to VA nonusers. More research on
veterans who do not use the VA for healthcare is needed to
obtain a fuller picture of Iraq and Afghanistan war veterans
and their healthcare needs.
Acknowledgments This research was supported by the Department
of Veterans Affairs (VA), Health Services Research and Development
(HSR&D) Service (Grant No. DHI-07-150) and the Department of
Defense (DoD) (Grant No. 08-2-0045). The sponsors were not
involved in any aspect of the study’s design and conduct; data col-
lection, management, analysis, or interpretation of data; or in the
preparation, review or approval of the manuscript. The findings and
conclusions presented in this manuscript are those of the authors and
do not necessarily represent the views of the VA, HSR&D, or DoD.
Conflict of interest The authors report no competing interests.
Open Access This article is distributed under the terms of the
Creative Commons Attribution License which permits any use, dis-
tribution, and reproduction in any medium, provided the original
author(s) and the source are credited.
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